To obtain the macroscale Young’s modulus of glutenite under gravel inclusions, a numerical simulation of macroscale Young’s modulus prediction based on the mesoscale characteristics of glutenite was carried out. Firstly, the micron indentation test was used to obtain the meso-mechanical parameters of gravel and matrix in glutenite to ensure the reasonableness of the numerical simulation parameter settings; secondly, a two-dimensional glutenite physical model generation method based on the secondary development of Python was put forward; and then, the macroscale Young’s modulus variation rule of glutenite under different gravel sizes, particle size ratios, and content characteristics were analyzed using the finite element method (FEM). The results show that Young’s modulus of gravel is larger than Young’s modulus of the matrix, and Young’s modulus of different gravel and matrix has some differences. The gravel content is the main controlling factor affecting the macroscale Young’s modul... [more]

Packed bed reactors play a crucial role in various industrial applications. This paper utilizes the Discrete Element Method (DEM), an efficient numerical technique for simulating the behavior of packed beds of particles as discrete phases. The focus is on generating densely packed particle beds. To ensure the model accuracy, specific DEM parameters were studied, including sub-step and rolling resistance. The analysis of the packed bed model extended to a detailed exploration of void fraction distribution along radial and vertical directions, considering the impact of wall interactions. Three different samples, spanning particle sizes from 0.3 mm to 6 mm, were used. Results indicated that the number of sub-steps significantly influences void fraction precision, a key criterion for comparing simulations with experimental results. Additionally, the study found that both loosely and densely packed beds of particles could be accurately represented by incorporating appropriate values for rol... [more]

In this paper, the dynamic deposition behavior of Na-enriching Zhundong coal ash on tube bundles with varying longitudinal and transverse pitches was numerically studied. By using a modified critical viscosity model, an improved CFD deposition model has been established and key parameters, including deposit mass and morphology, particle trajectories and impaction and sticking probabilities, as well as the heat flux distribution, have been analyzed. The results show that the ash deposited on tubes in the first row is, respectively, 1.74 and 3.80 times higher than that on the second and third rows, proving that ash deposition in the downstream is lessened. As the longitudinal pitch increased from 1.50 D to 2.50 D, deposit mass in the downstream increased two times, suggesting that an increase in longitudinal pitch would aggravate ash deposition. The effect of transverse pitch, however, with the least deposit propensity at St/D = 1.75, is non-linear due to the joint effect of adjacent tub... [more]

This paper is based on the surface defects of casting billets in the production process of nonoriented silicon steel plates at a steel plant in North China. Taking the parameters of a slab mold in the nonoriented silicon steel production process as a prototype, the flow field characteristics of the mold under the same section, different drawing speed and immersion depth were systematically studied by using a LES (large eddy simulation) and VOF (volume of fluid) coupling algorithm. The results show that under the current conditions, when the critical slag entrapment speed increases from 1.0 m/min to 1.2 m/min, the nozzle insertion depth increases linearly with the critical slag entrapment speed, while when the nozzle insertion depth exceeds 130 mm, the increasing effect of further increasing the nozzle insertion depth on the critical slag entrapment speed begins to decrease. When the drawing speed of continuous casting is kept constant at 1.4 m/min, the abnormal fluctuation height of th... [more]

Alzheimer’s disease has been a serious problem for humankind, one without a promising cure for a long time now, and researchers around the world have been working to better understand this disease mathematically, biologically and computationally so that a better cure can be developed and finally humanity can get some relief from this disease. In this study, we try to understand the progression of Alzheimer’s disease by modeling the progression of amyloid-beta aggregation, leading to the formation of filaments using the stochastic method. In a noble approach, we treat the progression of filaments as a random chemical reaction process and apply the Monte Carlo simulation of the kinetics to simulate the progression of filaments of lengths up to 8. By modeling the progression of disease as a progression of filaments and treating this process as a stochastic process, we aim to understand the inherent randomness and complex spatial−temporal features and the convergence of filament propagatio... [more]

The permeability of low-permeability cores is generally measured using a pulse decay method. The core of low-permeability rocks, such as shale, often has a layered structure. The applicability of pulse decay testing for layered cores is not clear. In this study, the performance of the pulse decay method on layered cores was comprehensively investigated. Numerical simulations were conducted to investigate the influence of the interlayer permeability ratio, storativity ratio, layer thickness, interlayer location, and number of layers on the pulse decay pressure and pressure derivative curves, as well as the permeability obtained from pulse decay testing. The results revealed that the pressure curves of layered cores exhibit distinct differences from those of homogeneous cores if the upstream permeability is larger than the downstream one. The pressure derivative curve shows more inclined or horizontal straight-line segments than in the homogeneous case. The shapes of the pressure and pre... [more]

A depressant is essential to the effective flotation-based separation of ilmenite and forsterite, based on their comparable physicochemical characteristics. In this work, dextran sodium sulfate (DSS) was initially introduced as a depressant, to aid in the separation of ilmenite and forsterite. Comparing the DSS to conventional natural starch, the results indicate that the forsterite exerts a greater depression over the ilmenite. The difference in recovery of ilmenite and forsterite was 75.44% at 10 mg/L of DSS dosage. The DSS was chemisorbed strongly onto the forsterite surface via Mg active sites, whereas its interaction with the ilmenite surface via physisorption was weak, based on the XPS and molecular-dynamics-simulation analyses. The results of the AFM and QCM-D investigations showed that the DSS adsorption layer on the forsterite surface was larger than those on the ilmenite surface. Consequently, DSS may function as a depressant, to effectively separate forsterite from ilmenite... [more]

In this work, the internal flow behaviour and characteristic pressure fluctuations of an axial pump with varying water conditions are analysed. The impact of tip vortex flow on the pattern of turbulent flow is simulated numerically by the application of the CFD technique and experimentally using an acoustics analysis method. The numerical CFD data are verified with an experimental test model for accuracy and reliability. Based on the results, the difference in pressure in the internal flow and at the surfaces of the blade can be impacted through tip leakage vortex regions, which leads to changes in internal flow. Subsequently, the flow in the clearance and tip leakage vortex regions is changed. Moreover, the results reveal that the suction wall upstream is more unsteady near the surface due to more mixing, secondary flow, and tip leakage vortices. Pressure fluctuation occurs near the tip of the blade, caused by the increasing vortex flow velocity and hence raising the turbulent kinetic... [more]

The bottomhole pressure is one of the key parameters for oilfield development and decision-making. However, due to factors such as cost and equipment failure, bottomhole pressure data is often lacking. In this paper, we established a GA-XGBoost model to predict the bottomhole pressure in carbonate reservoirs. Firstly, a total of 413 datasets, including daily oil production, daily water production, daily gas production, daily liquid production, daily gas injection rate, gas−oil ratio, and bottomhole pressure, were collected from 14 wells through numerical simulation. The production data were then subjected to standardized preprocessing and dimensionality reduction using a principal component analysis. The data were then split into training, testing, and validation sets with a ratio of 7:2:1. A prediction model for the bottomhole pressure in carbonate reservoirs based on XGBoost was developed. The model parameters were optimized using a genetic algorithm, and the average adjusted R-squar... [more]

Optimizing the structure of micromixers to improve the mixing efficiency is of great significance for chemical engineering and biology fields. In this study, an optimization of the microchannel in two liquids mixing is carried out based on computational fluid dynamics (CFD) and response surface methodology. Firstly, CFD simulations were performed to investigate the mixing flow field and mixing efficiency in the microchannel by considering different process and structure parameters (e.g., feed pressure p, microchannel width w). The response surface methodology was adopted to construct a fitting surface by CFD discrete working conditions. Then, an optimized microchannel width w was searched using the parallel particle swarm optimization (PPSO) algorithm from the response surface. Lastly, the searched optimum was validated by CFD simulation again, and the final result showed that the predicted mixing efficiency from the response surface model is well confirmed by CFD simulation. On averag... [more]

Shale oil resources, noted for their broad distribution and significant reserves, are increasingly recognized as vital supplements to traditional oil resources. In response to the high fracturing costs and swift decline in productivity associated with shale oil horizontal wells, this research introduces a novel approach utilizing CO2 for enhanced shale oil recovery in radial boreholes. A compositional numerical simulation method is built accounted for component diffusion, adsorption, and non-Darcy flow, to explore the viability of this technique. The study examines how different factors—such as initial reservoir pressure, permeability, numbers of radial boreholes, and their branching patterns—influence oil production and CO2 storage. Our principal conclusions indicate that with a constant CO2 injection rate, lower initial reservoir pressures predominantly lead to immiscible oil displacement, hastening the occurrence of CO2 gas channeling. Therefore, maintaining higher initial or inject... [more]

A pumping-while-tripping method is proposed to mitigate pressure swabs during tripping out in wells with a narrow mud density window and extended reach. In the proposed tripping-out process, the fluid circulation is started by using a special pump from a customized circulation line before tripping is initiated. During the tripping out, drilling fluid is circulated in the wellbore simultaneously while the drilling string is moving. A model to simulate the dynamic pressure changes in this process is developed based on the Navier−Stokes (N-S) equations and a damped free vibration system. The model was initially developed for Herschel−Bulkley (H-B) fluid; however, it can be applied to other fluid models by eliminating the non-existing terms. An analysis was conducted to investigate the effect of tripping velocity and circulation pumping rate on the pressure changes. The results show that pumping-while-tripping is effective in mitigating the pressure swab during tripping out, which is espec... [more]

Due to the growth in the consumption of avocado in recent years, the amount of waste caused by avocado peel and seed has increased. Avocado waste can be transformed into valuable products such as energy, biofuels, and biological products using integrated processes in a biorefinery. This paper considers the detailed modeling, simulation, and optimization of a biorefinery for the production of phenolic compounds, bioethanol, biological xylitol, syngas, and electrical power from avocado seed and peel, using Aspen Plus in equation-oriented mode as a process simulation tool. For a biorefinery in nominal conditions, it is possible to achieve a gross profit of approximately 30×106 USD/year for capital costs of USD 31.4×106, while the combined effect of process optimization and heat integration allows reaching a gross profit of 37×106 USD/year for capital costs of USD 30.7×106. These results of the optimized plant show its potential to take advantage of avocado seed and peel in a profitable an... [more]

A prevalent metal surface defect is hot-rolled iron oxide; thus, it is critical to regulate the production and growth of oxidized iron during the hot-rolling process. To analyze the influence of Si content on the growth laws of the oxidized layer in carbon steel during heating, three types of carbon steel with significant differences in Si content were selected for research on the growth laws of the oxidized layer at different heating temperatures. The production law and micromorphology of the oxidized layer were analyzed using methods such as scanning electron microscopy and thermodynamic phase diagram calculation, and an oxidation dynamic model was obtained. The predicted control values of the model are highly consistent with the measured values. This study reveals that the heating temperature significantly impacts the thickness of the oxidized layer of carbon steel. At temperatures below 500 °C, the oxidation is not evident, and the layer is thin. Between 500 °C and 900 °C, the stee... [more]

The problems of large deformations, failures, and fractures that agricultural tillage tools may encounter during the cultivation process has long been a concern in the field of agricultural machinery design and manufacturing. It is important to establish a more accurate numerical model to effectively predict tools’ plastic deformation failures and ductile fracture failures. This research develops a numerical model for predicting the plastic deformation failure and ductile fracture failure of agricultural tillage tools using the smoothed particle hydrodynamics (SPH) method and the Johnson−Cook constitutive model. The model uses the Drucker−Prager criterion to describe the elastic−plastic constitutive behavior of the soil, the von Mises criterion to describe the Johnson−Cook constitutive model of the tool, and the coupling condition with the Lennard-Jones repulsive force to describe the interaction between the tool and soil. The numerical results show that the proposed model can effectiv... [more]

Parallel seam welding (PSW) is the most commonly employed encapsulation technology to ensure hermetic sealing and to safeguard sensitive electronic components. However, the PSW process is complicated by the presence of multiphysical phenomena and nonlinear contact problems, making the analysis of the dynamics of the PSW process highly challenging. This paper proposes a multiphysics simulation model based on direct coupling, enabling the concurrent coupling of the electric field, temperature field, and structural field to facilitate the analysis of the thermal and electrical dynamics within the PSW process. First, this paper conducts an in-depth theoretical analysis of thermal and electrical contact interactions at all contact interfaces within the PSW process, taking into account material properties related to temperature. Second, the acquired data are integrated into a geometric model encompassing electrode wheels and ceramic packaging components, facilitating a strongly coupled multi... [more]

The utilization of auxiliary tools employing ultrasonic high-frequency vibration to enhance rock breaking efficiency holds significant potential for application in underground hard rock excavation engineering. To investigate the failure mechanism of rocks under high frequency ultrasonic vibration load, this study employs particle flow software PFC2D for numerical simulation. By incorporating boundary conditions from actual ultrasonic vibration rock breaking experiments and utilizing a parallel bond model to construct the rock, we analyze the deformation, damage, fracture, and energy evolution process of hard rocks subjected to vibrational loads. The results demonstrate that the maximum displacement in hard rocks increases nearly linearly with vibrations until reaching 5.0199 × 10−3 m, after which it plateaus. Additionally, macroscopic fissures formed during rock failure exhibit an X-shaped pattern. Furthermore, based on our model, we examine the impact of amplitude variation on hard ro... [more]

Gas leaks can cause disasters at process sites, including fires and explosions, and thus, effective gas-leak detection systems are required. This study investigated the limitations of conventional detectors and introduced an innovative ultrasonic sensor-based approach for continuous monitoring. A new configuration for a stationary remote ultrasonic gas-leak monitoring system is proposed. The selected material was 1-Butene. The detection probability was assessed through a simulation based on a gas-leak scenario, detailing the selection criteria for leak sites and simulation conditions. Computational fluid-dynamics (CFD) simulations were used to evaluate the detection capability of the existing system, whereas Monte Carlo simulations were used to compare it with the proposed ultrasonic system. The CFD simulation was performed by setting the lower detection limit of the concentration-measurement-type gas detector to 600 ppm, and the leak-detection time was approximately 8.895 s. A Monte C... [more]

The rational structural design of polycrystalline diamond compact (PDC) cutters effectively enhances the performance of drill bits in rock fragmentation and extends their service life. Inspired by bionics, a bionic PDC cutter was designed, taking the mole claw toe, shark tooth, and microscopic biomaterial structures as the bionic prototypes. To verify its rock-breaking effectiveness, the finite element method was employed to compare the rock-breaking processes of the bionic cutter, triangular prism cutter, and axe cutter. The study also investigated the influence of different back rake angles, cutting depths, arc radii, and hydrostatic pressures on rock breaking using the bionic cutter. Prior to this, the accuracy of the finite element model was validated through laboratory tests. Subsequently, a drill bit incorporating all three types of cutters was constructed, and simulations of rock breaking were conducted on a full-sized drill bit. The results demonstrate that the bionic cutter ex... [more]

It is important for data modeling to comply with a data observation window of physical variables behind the data. In this paper, a multivariate data alignment method is proposed to follow different time scales and different role effects. First, the length of the sliding windows is determined by the frequency characteristics of the time-series reconstruction. Then, the time series is aligned to the length of the window by a sequence-to-sequence neural network. This neural network is trained by replacing the loss function with dynamic time warping (DTW) in order to prevent the losses of the time series. Finally, the attention mechanism is introduced to adjust the effect of different variables, which ensures that the data model of the matrix is in accord with the intrinsic relation of the actual system. The effectiveness of the approach is demonstrated and validated by the Tennessee Eastman (TE) model.

This study reports a novel hybrid model for the prediction of six critical process variables of importance in an industrial-scale FCC (fluid catalytic cracking) riser reactor: vacuum gas oil (VGO) conversion, outlet riser temperature, light cycle oil (LCO), gasoline, light gases, and coke yields. The proposed model is developed via the integration of a computational particle-fluid dynamics (CPFD) methodology with artificial intelligence (AI). The adopted methodology solves the first principle model (FPM) equations numerically using the CPFD Barracuda Virtual Reactor 22.0® software. Based on 216 of these CPFD simulations, the performance of an industrial-scale FCC riser reactor unit was assessed using VGO catalytic cracking kinetics developed at CREC-UWO. The dataset obtained with CPFD is employed for the training and testing of a machine learning (ML) algorithm. This algorithm is based on a multiple output feedforward neural network (FNN) selected to allow one to establish correlations... [more]

Effectively managing the quality of iron ore is critical to iron and steel metallurgy. Although quality inspection is crucial, the perspective of sintered surface identification remains largely unexplored. To bridge this gap, we propose a deep learning scheme for mining the necessary information in sintered images processing to replace manual labor and realize intelligent inspection, consisting of segmentation and classification. Specifically, we first employ a DeepLabv3+ semantic segmentation algorithm to extract the effective material surface features. Unlike the original model, which includes a high number of computational parameters, we use SqueezeNet as the backbone to improve model efficiency. Based on the initial annotation of the processed images, the sintered surface dataset is constructed. Then, considering the scarcity of labeled data, a semi-supervised deep learning scheme for sintered surface classification is developed, which is based on pseudo-labels. Experiments show th... [more]

Aiming at addressing the problem of dust generated when grab is unloaded, the flow field characteristics of fugitive dust in an open space were studied and reflected its unstable and complex nonlinear dynamic process. Using coal, sand, and flour as research objects, an experimental model and measurement system for grab unloading were built, and the dust diffusion range, diffusion speed and direction, settling time, dust concentration, and induced wind velocity at different measurement points were compared. The computational fluid dynamics−discrete element method (CFD-DEM) coupling method was adopted, the discrete phase model (DPM) of dust was established, the interaction of the particle, dust, and airflow fields during the unloading process of the grab was further studied, and the distribution and diffusion laws of the induced airflow and dust were obtained. The acquisition of flow field characteristics is of great significance for controlling and guiding the orderly deposition of dust... [more]

Recently, theoretical modeling based on rock physics has emerged as a pivotal approach to studying the resistivity of complex fractured−cavernous microstructures. In this work, to study the effects of fractured−cavernous structures on carbonate reservoir resistivity, electrical conductivity models were developed based on the effective medium theory and Ohm’s Law, and theoretical simulations were performed to examine how the porosity and resistivity of the rock matrix, the formation water resistivity, and the parameters of the fractured−cavernous microstructure affect the resistivity of rocks saturated with petroleum or water. Furthermore, the modeling results revealed the specific relationships between these factors in petroleum-saturated and water-saturated rocks. For vuggy reservoirs, a significant negative correlation between throat diameter and resistivity was revealed when variations in the rock matrix and formation water resistivity were negligible. Furthermore, the pore shape—es... [more]

The worldwide demand for customized centrifugal pumps in numerous industries is intensifying steadily, posing significant challenges to the traditional design model characterized by extended design cycles, numerous errors, and elevated development costs. To address these issues, this paper introduces an intelligent collaborative design methodology for industrial centrifugal pumps grounded in digital twin (DT) technology. The methodology aims to handle the diversified types and intricate design requirements of industrial pumps and is specifically tailored to predict pump performance through a detailed multi-physics model. This model encapsulates various physical processes, including fluid dynamics, thermodynamics, and structural mechanics, and incorporates the designer’s professional knowledge and experience to support enhanced decision-making. Furthermore, the application of intelligent parametric models has facilitated the interconnected design of pump components. This advancement has... [more]